1. Field of the Invention
The invention relates to the field of identity authentication. More specifically, the invention relates to systems and methods of identity authentication by voice biometric verification.
2. Description of Related Art
Modern commercial transactions are becoming increasingly susceptible to identity theft, especially for remote transactions in which there is little or no direct personal contact between the consumer and the goods or services provider (GSP). Identity theft occurs whenever an unauthorized individual is granted access to or approved for a transaction while using someone else's identity, or unauthorized access to physical files, PCs/PDAs, employee records, and the like. It is a worldwide problem whose annual cost currently exceeds $200 billion. This problem threatens the further adoption of consumer-driven, self-service, and cost-savings technologies, negatively affects customer relationships and brand value, erodes profit margins, drives new legislative burdens, and increases the threat of new litigation.
Various methods of identity authentication have been implemented conventionally, including the use of passwords, access cards, and the like. The chief difficulty with such identity indicators is that they are subject to loss or theft.
One more recent type of indicator in use in the identity authentication industry is that of the individual's voice. In a typical voice biometric system, a consumer provides a voice sample when signing up or enrolling for a service, and when a bank, merchant, or customer wishes to have a consumer's identity verified at a subsequent time, the consumer is asked to provide a current sample which is compared against the stored sample. If the samples match within certain parameters, the current sample is deemed to pass the authentication or verification test, indicating that the instant speaker is the same person who provided the baseline voice sample.
Voice authentication is based on the fact that the characteristics of each person's voice differ in terms of pitch, tone, volume, and other characteristics. These differences make the voice uniquely distinguishable and the chance that all of these are exactly the same in any two people extremely low. An individual's voiceprint is as unique to them as his or her fingerprint.
Voice authentication is not the same as speech recognition. Speech recognition is the process of identifying what words have been spoken, not identifying who spoke them. Speech recognition can be used in combination with voice authentication to make it more powerful. For example, if the user is required to speak a password, the voice biometric can confirm the person's identity, and speech recognition can be used to validate that the password given is correct. The combination of the two creates a highly accurate authentication mechanism.
With voice authentication, the voice characteristics (data) are processed by the use of algorithms that authenticate the voice. All of the algorithms use some combination of time and frequency to determine whether two voice samples match.
Voice authentication works by comparing two different samples of an individual's voice. The reference sample is one where the identity of the speaker is tied to the sample itself (i.e.; this is John Doe's voice). A second voice sample is then compared to John Doe's reference sample. There are two approaches to comparing the voice samples, text dependent and text independent.
“Text dependent” means that the two voiceprints being compared must be the same words or phrases as were previously captured. Example: John Doe speaks the phrase “serendipity today” and it is compared to a recording of someone speaking that same phrase. This is the more simple of the two because the patterns being compared will match more closely.
The second approach is text independent, meaning that the two voiceprints are not necessarily of the same words or phrases. Example: John Doe's speech patterns are captured and compared to someone speaking conversationally. In this case, the analysis attempts to find common patterns between the two samples within the words. Text independent analysis requires a longer sample to compare.
A number of different voice biometric systems have been described, for example, U.S. Pat. No. 6,934,849 to Kramer et al., U.S. Pat. No. 6,920,435 to Hoffman et al., U.S. patent application Ser. No. 2005/0138391 to Mandalia et al., U.S. patent appl'n Ser. No. 2004/0010698 to Rolfe, the teachings of which are hereby incorporated by reference herein. Conventional voice identity authentication methods such as these typically require that additional, customized hardware (computer and telephony devices) be purchased, configured, and placed within the customer's own computing environment. This adds considerable expense to the identity validation process, as well as on-going training, maintenance, data storage, compliance, and other burdens on the customer. These conventional systems also are inflexible in configuration, offering essentially the same type of identity challenge to each individual. However, different institutional customers may require very different authentication solutions; indeed, a single customer may require a variety of different levels of authentication for its different categories of consumers.